This research explores the effects of exogenous variables on AIML Predictive Algorithm Prophet, such as macroeconomic changes, population trends in relevant regions and disruptions, on the efficacy and accuracy of AIML forecasting algorithms for product demand in the FMCG industry. This study will identify which external factors most influence demand forecasting, revealing potential gaps in current AI/ML prediction models. They can lead to better business decision-making, risk mitigation, and industry adaptation for disruptions.
Research Approach (methodology): Gather data on product demand and relevant exogenous variables, develop and train AI/ML algorithms, and assess predictive accuracy when these variables are considered versus when they’re excluded.
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